New dcm methods for ml, and pattern identification in biogeography

PI(s):

Ganeshkumar Ganapathy

Start Date:

1-Dec-2006

End Date:

30-Nov-2009

Keywords:

maximum likelihood, biogeography, computational modeling

I propose to develop new software for heuristic
maximum likelihood (ML) estimation
to obtain better results on large datasets more
efficiently.
I propose to design and implement disk-covering methods
(DCM) for maximum likelihood. Disk-covering methods are divide-and-conquer
algorithmic techniques and have recently been applied with a lot of success
to maximum parsimony

Simultaneously,
I propose to design and implement new algorithms for identifying
common patterns in area cladograms occurring in biogeography. Common
patterns observed among area cladograms of different groups of species in
the same region can give valuable insights about the processes that led to
the current geographic distribution of species.